The overall goal of this project is to identify genes affecting common forms of human obesity. We have accrued samples of obese cases, normal weight controls and families segregating extreme obesity and normal weight. In this application, we propose a fine-grained association scan for a limited segment of the genome that has been highly selected to maximize the prior probability of identifying genes. The samples are unique, the target region is well supported, and the methods of genotyping and analysis will be state of the art. Finally, the two- stage approach using cases and controls followed by families enhances the power to identify causative genes while minimizing the chance of false positives. We propose to conduct a ~2kb association scan of a ~12.9mb genomic region identified in our previous work on chromosome 10p12. This region was chosen for several reasons: It is strongly linked to obesity related phenotypes in our samples;the linkages have been replicated by others;we and others have identified associations to genomic sequence in these regions but these associations do not account for the linkage signal, suggesting multiple genes may account for the quantitative trait locus (QTL) in this region. Finally, our linkage results and bioinformatics analyses of mouse and human sequence suggest that one or more obesity related genes in this region may be imprinted. Specifically, we will: 1. conduct an association scan across ~12.9 mb of chromosome 10p12 in obese cases and normal weight controls;2. use family based methods to replicate positive results from case-control analyses;3. genotype and analyze for association all common SNPs in the regions, including coding and possible regulatory sequence;4. conduct exploratory association analyses of families incorporating parent of origin. Obesity is an increasingly prevalent condition having serious consequences for health and quality of life. The identification of genes for common forms of human obesity should lead to more individualized therapies and more effective prevention strategies. The overall goal of this project is to identify genes affecting common forms of human obesity through association analyses using cases, controls and families. Obesity is an increasingly prevalent condition having serious consequences for health and quality of life. The identification of genes for common forms of obesity should lead to more individualized therapies and more effective prevention strategies.